Target Validation
Validate a candidate target by holding your own experimental data up against the published record. Inflexa runs rigorous multi-method analysis on your omics, then assembles a tier-by-tier literature evidence chain (basic biology, preclinical, clinical) from targeted PubMed queries and public databases. The platform overlays the two: where your findings converge with the published record, where they contradict it, and where the translational chain has gaps that would derail an advancement decision.
Deliverables
Evidence convergence map
A side-by-side view showing where your experimental findings align with published literature. Each convergence point links your differential expression or pathway result to a literature evidence claim, with the source papers, databases, and confidence scores that support it. Convergent signals between independent data sources are the strongest basis for target advancement decisions.
Contradiction report
Not all evidence agrees. The contradiction report surfaces findings where your results conflict with published literature or where the literature itself is divided. Each conflict is contextualized by species, model system, and disease stage, so you can assess whether the disagreement is meaningful or explained by experimental differences. For GLP1R, the platform identified conflicting evidence for AP2M1 (concordance 0.42) and coronary artery disease (concordance 0.33).
Translational gap analysis
A staged view of evidence across the translational chain: basic research, preclinical, and clinical. The analysis highlights where evidence is strong, where it thins out, and where gaps could derail a program. For GLP1R, evidence coverage is complete across all three stages, a strong signal for target maturity. For earlier-stage targets, this analysis identifies exactly where additional experiments are needed.
Advance or deprioritize targets based on convergent evidence from your data and the full published record. Targets with strong convergence across independent data sources and complete translational chains are the strongest advancement candidates.
GLP1R target validation: evidence integration
| Literature Signal | Analysis Finding | Cell Context | Verdict |
|---|---|---|---|
| Inflammation (0.90) | TNFα/NF-κB NES 2.27 | IL-33 mast cells | Convergent |
| Obesity (0.81) | IL2/STAT5 NES 1.89 | IL-4 eosinophils | Convergent |
| Type 2 Diabetes (0.81) | Insulin secretion 0.70 | GLP1R pathway | Convergent |
| Entity | Concordance | Type |
|---|---|---|
| AP2M1 | 0.42 | Molecular interaction |
| Coronary Artery Disease | 0.33 | Disease association |
CROSS-TARGET COMPARISON: EGFR (ONCOLOGY)
EGFR has 7.2x more clinical trials (2,293 vs 317) reflecting oncology's trial-intensive development model. GLP1R has broader disease associations (286 vs 148) spanning metabolic, cardiovascular, and CNS indications.
| Indication | Score | Evidence Basis |
|---|---|---|
| NSCLC | 0.77 | clinical + human |
| GBM | 0.70 | clinical + human |
| CRC | 0.70 | clinical + human |
| Molecular Partner | Interaction Score |
|---|---|
| EGF | 0.97 |
| STAT3 | 0.92 |
| PTPN1 | 0.90 |
| PTPN11 | 0.86 |
| AP2M1 | 0.83 |
Methodology
Assemble a literature evidence chain for the target
Inflexa runs targeted PubMed queries scoped to the target, then enriches with public sources (ChEMBL, Open Targets, ClinicalTrials.gov, FAERS, STRING). Each evidence claim carries a hyperlink to its supporting PMID or record. For GLP1R, this yielded 251 papers, 1,301 evidence items, and 317 clinical trials, organised into a basic-biology / preclinical / clinical chain.
Run differential expression
Inflexa analyzes your experimental omics data using DESeq2 with appropriate covariates. For the IL-4/IL-13/IL-33 dataset, this identified 4,272 differentially expressed genes across 62 samples in two cell types.
Pathway enrichment identifies biological processes
GSEA enrichment across Hallmark, KEGG, and Reactome gene sets identifies which biological processes are affected. The platform found TNFα/NF-κB signaling as the top IL-33 pathway (NES 2.27) and IL2/STAT5 as the top IL-4 pathway (NES 1.89).
Platform overlays results to find convergence
Literature disease associations are matched against experimental pathway and gene-level findings. Convergent signals (where independent evidence sources agree) are flagged as high-confidence. Contradictions are surfaced with concordance scores.
Translational gap analysis
Evidence is mapped across the translational chain (basic research → preclinical → clinical). Gaps at any stage are flagged. For GLP1R, the chain is complete with 580 basic research items, 404 preclinical items, and 317 clinical items.
Target personas
Target biology lead
Assess whether experimental findings are consistent with the broader evidence base before committing to validation studies.
Translational science head
Identify translational gaps and contradictions that could derail programs, before they become expensive.
Portfolio reviewer
Compare targets by evidence maturity and convergence strength to allocate resources effectively.
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